Ying Zhang1,2, Wei Zhang1,2, Xinglan Li1,2, Dapeng Li1, Xiaoling Zhang1, Yajie Yin1,2, Xiangyun Deng1,2, Xiugui Sheng3. 1. Department of Gynecologic Oncology, Shandong Cancer Hospital and Institute, 440 Jiyan Road, Jinan, 250117, Shandong, People's Republic of China. 2. School of Medicine and Life Sciences, University of Jinan, Shandong Academy of Medical Sciences, 106 Jiwei Road, Jinan, 250022, Shandong, People's Republic of China. 3. Department of Gynecologic Oncology, Shandong Cancer Hospital and Institute, 440 Jiyan Road, Jinan, 250117, Shandong, People's Republic of China. shengxiugui@163.com.
Abstract
BACKGROUND: Endometrial cancer (EC) is the most prevalent malignancy worldwide. Although several efforts had been made to explore the molecular mechanism responsible for EC progression, it is still not fully understood. AIM OF THE STUDY: To evaluate the clinical characteristics and prognostic factors of patients with EC, and further to search for novel genes associated with EC progression. METHODS: We recruited 328 patients with EC and analyzed prognostic factors using Cox proportional hazard regression model. Further, a gene expression profile of EC was used to identify the differentially expressed genes (DEGs) between normal samples and tumor samples. Subsequently, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis ( http://www.genome.jp/kegg/ ) for DEGs were performed, and then protein-protein interaction (PPI) network of DEGs as well as the subnetwork of PPI were constructed with plug-in, MCODE by mapping DEGs into the Search Tool for the Retrieval of Interacting Genes database. RESULTS: Our results showed that body mass index (BMI), hypertension, myometrial invasion, pathological type, and Glut4 positive expression were prognostic factors in EC (P < 0.05). Bioinformatics analysis showed that upregulated DEGs were associated with cell cycle, and downregulated DEGs were related to MAPK pathway. Meanwhile, PPI network analysis revealed that upregulated CDK1 and CCNA2 as well as downregulated JUN and FOS were listed in top two nodes with high degrees. CONCLUSIONS: Patients with EC should be given more focused attentions in respect of pathological type, BMI, hypertension, and Glut4-positive expression. In addition, CDK1, CCNA2, JUN, and FOS might play important roles in EC development.
BACKGROUND:Endometrial cancer (EC) is the most prevalent malignancy worldwide. Although several efforts had been made to explore the molecular mechanism responsible for EC progression, it is still not fully understood. AIM OF THE STUDY: To evaluate the clinical characteristics and prognostic factors of patients with EC, and further to search for novel genes associated with EC progression. METHODS: We recruited 328 patients with EC and analyzed prognostic factors using Cox proportional hazard regression model. Further, a gene expression profile of EC was used to identify the differentially expressed genes (DEGs) between normal samples and tumor samples. Subsequently, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis ( http://www.genome.jp/kegg/ ) for DEGs were performed, and then protein-protein interaction (PPI) network of DEGs as well as the subnetwork of PPI were constructed with plug-in, MCODE by mapping DEGs into the Search Tool for the Retrieval of Interacting Genes database. RESULTS: Our results showed that body mass index (BMI), hypertension, myometrial invasion, pathological type, and Glut4 positive expression were prognostic factors in EC (P < 0.05). Bioinformatics analysis showed that upregulated DEGs were associated with cell cycle, and downregulated DEGs were related to MAPK pathway. Meanwhile, PPI network analysis revealed that upregulated CDK1 and CCNA2 as well as downregulated JUN and FOS were listed in top two nodes with high degrees. CONCLUSIONS:Patients with EC should be given more focused attentions in respect of pathological type, BMI, hypertension, and Glut4-positive expression. In addition, CDK1, CCNA2, JUN, and FOS might play important roles in EC development.
Authors: Alice Bradfield; Lucy Button; Josephine Drury; Daniel C Green; Christopher J Hill; Dharani K Hapangama Journal: Methods Protoc Date: 2020-09-03